Survey: Few Americans Want Government to Limit Use of Facial Recognition Technology, Particularly for Public Safety or Airport Screening

Only one in four Americans (26 percent) think government should strictly limit the use of facial recognition technology, according to a new survey from the Center for Data Innovation—and that support drops even further if it would come at the expense of public safety. Fewer than one in five Americans (18 percent) would agree with strictly limiting the technology if that is the tradeoff, while a solid majority (55 percent) would disagree.

Similarly, only 20 percent of Americans say government should strictly limit use of facial recognition if it would mean airports can’t use the technology to speed up security lines, while a 54 percent majority would disagree with such a limit. And just 24 percent want strict limits if it would prevent stores from using the technology to stop shoplifting, while 49 percent would oppose such a tradeoff.

There were some differences in these opinions based on age, with older Americans more likely to oppose government limits on the technology. For example, 52 percent of 18 to 34-year-olds opposed limitations that come at the expense of public safety, compared to 61 percent of respondents ages 55 and older. In addition, women were less likely to support limits than men. For example, only 14 percent of women support strictly limiting facial recognition if it comes at the expense of public safety, versus 23 percent of men.

Table 2: U.S. Internet users’ opinions on facial recognition technology, by age and gender.

The survey asked whether police should be allowed to use facial recognition to help find suspects. Support for using the technology that way increases depending on its accuracy: If the software is right 80 percent of the time, then 39 percent agree with using it and 32 percent disagree. If the software is right 90 percent of the time, then 47 percent of respondents agree with using it and 25 percent disagree. And if the software is right 100 percent of the time, then 59 percent agree with using it, while 16 percent disagree.

Table 3: U.S. Internet users’ opinions on use of facial recognition technology by police.

The survey also asked respondents whether government should limit surveillance cameras, since they are integral to many applications of facial recognition technology. Overall, Americans were more likely to support limiting surveillance cameras (36 percent) than facial recognition technology (26 percent). But that flips when respondents are asked about tradeoffs. For example, if it would mean stores couldn’t use the technology to stop shoplifting, then support for limits on surveillance cameras drops by half, from 36 percent to just 18 percent, while support for limits on facial recognition slips only slightly from 26 percent to 24 percent.

If it would come at the expense of public safety, then just 18 percent of Americans would agree with limiting surveillance cameras and the same percentage would agree for facial recognition. These findings suggest that what little support there is for limiting facial recognition technology is related to existing support for limiting the use of surveillance cameras.

Detailed Survey Results

Survey Methodology

The Center for Data Innovation conducted a national online poll of 3,151 U.S. adult Internet users between December 13, 2018 and December 16, 2018. Using Google Surveys, we applied weights to each response to match the breakdowns of age, gender, and region to those demographic breakdowns in the national Internet population as estimated by the U.S. Census Bureau’s 2015 Current Population Survey (CPS) Computer and Internet Use Supplement.

Multiple analyses have found Google Surveys to be a useful survey tool. In 2012, the Pew Research Center compared the results for 43 questions it asked through telephone surveys and Google Surveys, finding that the median difference between the two methods’ results was three percentage points. Moreover, Google Surveys accurately predicted the 2012 presidential election. Lastly, a 2016 analysis, published in the peer-reviewed journal Political Analysis by Rice University political scientists, replicated four canonical social science experiments with Google Surveys and concluded that Google Surveys “is likely to be a useful platform for survey experimenters doing rigorous social scientific work.”

Google Surveys donated the use of its platform for this research but played no role in the findings or in developing the questions. To learn more about Google Surveys’ methodology and accuracy, please see the Google Surveys Whitepaper and a study comparing Google Surveys to other Internet surveys.

About the Center for Data Innovation

The Center for Data Innovation conducts high-quality, independent research and educational activities on the impact of the increased use of information on the economy and society. In addition, the Center for Data Innovation formulates and promotes pragmatic public policies designed to enable data-driven innovation in the public and private sector, create new economic opportunities, and improve quality of life. The Center is a nonprofit, nonpartisan research institute affiliated with the Information Technology and Innovation Foundation.

Daniel Castro is the director of the Center for Data Innovation and vice president of the Information Technology and Innovation Foundation. Mr. Castro writes and speaks on a variety of issues related to information technology and internet policy, including data, privacy, security, intellectual property, internet governance, e-government, and accessibility for people with disabilities. His work has been quoted and cited in numerous media outlets, including The Washington Post, The Wall Street Journal, NPR, USA Today, Bloomberg News, and Businessweek. In 2013, Mr. Castro was named to FedScoop’s list of “Top 25 most influential people under 40 in government and tech.” In 2015, U.S. Secretary of Commerce Penny Pritzker appointed Mr. Castro to the Commerce Data Advisory Council.
Mr. Castro previously worked as an IT analyst at the Government Accountability Office (GAO) where he audited IT security and management controls at various government agencies. He contributed to GAO reports on the state of information security at a variety of federal agencies, including the Securities and Exchange Commission (SEC) and the Federal Deposit Insurance Corporation (FDIC). In addition, Mr. Castro was a Visiting Scientist at the Software Engineering Institute (SEI) in Pittsburgh, Pennsylvania where he developed virtual training simulations to provide clients with hands-on training of the latest information security tools. He has a B.S. in Foreign Service from Georgetown University and an M.S. in Information Security Technology and Management from Carnegie Mellon University.

Michael McLaughlin is a research assistant at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.